# Masakhane -- Machine Translation For Africa

arXiv: https://arxiv.org/abs/2003.11529 · HTML: https://mlsanity.com/paper/2003.11529/

## Key facts

- Cited by 49 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Mar 2020.

## Built on by (most cited first, 30 of 49)

- [Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model](https://mlsanity.com/paper/2402.07827/) (2024)
- [Survey of Low-Resource Machine Translation](https://mlsanity.com/paper/2109.00486/) (2021)
- [POTATO: The Portable Text Annotation Tool](https://mlsanity.com/paper/2212.08620/) (2022)
- [Data Governance in the Age of Large-Scale Data-Driven Language Technology](https://mlsanity.com/paper/2206.03216/) (2022)
- [Opportunities and Challenges of Large Language Models for Low-Resource Languages in Humanities Research](https://mlsanity.com/paper/2412.04497/) (2024)
- [AfroMT: Pretraining Strategies and Reproducible Benchmarks for Translation of 8 African Languages](https://mlsanity.com/paper/2109.04715/) (2021)
- [A Material Lens on Coloniality in NLP](https://mlsanity.com/paper/2311.08391/) (2023)
- [AI4D -- African Language Program](https://mlsanity.com/paper/2104.02516/) (2021)
- [InkubaLM: A small language model for low-resource African languages](https://mlsanity.com/paper/2408.17024/) (2024)
- [Toward More Meaningful Resources for Lower-resourced Languages](https://mlsanity.com/paper/2202.12288/) (2022)
- [KenSwQuAD -- A Question Answering Dataset for Swahili Low Resource Language](https://mlsanity.com/paper/2205.02364/) (2022)
- [MMTAfrica: Multilingual Machine Translation for African Languages](https://mlsanity.com/paper/2204.04306/) (2022)
- [The Future of Open Human Feedback](https://mlsanity.com/paper/2408.16961/) (2024)
- [Kencorpus: A Kenyan Language Corpus of Swahili, Dholuo and Luhya for Natural Language Processing Tasks](https://mlsanity.com/paper/2208.12081/) (2022)
- [Low-Resource Neural Machine Translation for Southern African Languages](https://mlsanity.com/paper/2104.00366/) (2021)
- [Multilingual transfer of acoustic word embeddings improves when training on languages related to the target zero-resource language](https://mlsanity.com/paper/2106.12834/) (2021)
- [Neural Machine Translation for the Indigenous Languages of the Americas: An Introduction](https://mlsanity.com/paper/2306.06804/) (2023)
- [Socially Responsible Data for Large Multilingual Language Models](https://mlsanity.com/paper/2409.05247/) (2024)
- [The NaijaVoices Dataset: Cultivating Large-Scale, High-Quality, Culturally-Rich Speech Data for African Languages](https://mlsanity.com/paper/2505.20564/) (2025)
- [The first large scale collection of diverse Hausa language datasets](https://mlsanity.com/paper/2102.06991/) (2021)
- [Crowdsourced Phrase-Based Tokenization for Low-Resourced Neural Machine Translation: The Case of Fon Language](https://mlsanity.com/paper/2103.08052/) (2021)
- [Evaluating Self-Supervised Speech Representations for Indigenous American Languages](https://mlsanity.com/paper/2310.03639/) (2023)
- [Standard Language Ideology in AI-Generated Language](https://mlsanity.com/paper/2406.08726/) (2024)
- [Domain-specific MT for Low-resource Languages: The case of Bambara-French](https://mlsanity.com/paper/2104.00041/) (2021)
- [Missing Melodies: AI Music Generation and its "Nearly" Complete Omission of the Global South](https://mlsanity.com/paper/2412.04100/) (2024)
- [GhanaNLP Parallel Corpora: Comprehensive Multilingual Resources for Low-Resource Ghanaian Languages](https://mlsanity.com/paper/2603.13793/) (2026)
- [NusaCrowd: A Call for Open and Reproducible NLP Research in Indonesian Languages](https://mlsanity.com/paper/2207.10524/) (2022)
- [How much speech data is necessary for ASR in African languages? An evaluation of data scaling in Kinyarwanda and Kikuyu](https://mlsanity.com/paper/2510.07221/) (2025)
- [Reflections and New Directions for Human-Centered Large Language Models](https://mlsanity.com/paper/2605.06901/) (2026)
- [Contextual Text Embeddings for Twi](https://mlsanity.com/paper/2103.15963/) (2021)

## Abstract (arXiv)

Africa has over 2000 languages. Despite this, African languages account for a small portion of available resources and publications in Natural Language Processing (NLP). This is due to multiple factors, including: a lack of focus from government and funding, discoverability, a lack of community, sheer language complexity, difficulty in reproducing papers and no benchmarks to compare techniques. To begin to address the identified problems, MASAKHANE, an open-source, continent-wide, distributed, online research effort for machine translation for African languages, was founded. In this paper, we discuss our methodology for building the community and spurring research from the African continent, as well as outline the success of the community in terms of addressing the identified problems affecting African NLP.